Generating code-switched text is a problem of growing interest, especially given the scarcity
of corpora containing large volumes of real code-switched text. In this work, we adapt a state …

Code-mixed languages are very popular in multilingual societies around the world, yet the
resources lag behind to enable robust systems on such languages. A major contributing …

While code-mixing is a common linguistic practice in many parts of the world, collecting high-
quality and low-cost code-mixed data remains a challenge for natural language processing …

Data sparsity is a main problem hindering the development of code-switching (CS) NLP
systems. In this paper, we investigate data augmentation techniques for synthesizing …

Task-oriented dialogue research has mainly focused on a few popular languages like
English and Chinese, due to the high dataset creation cost for a new language. To reduce …

Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the
code-mixing phenomenon in Indonesian is limited, despite many languages being …

In this paper, we present an overview of the WMT 2022 shared task on code-mixed machine
translation (MixMT). In this shared task, we hosted two code-mixed machine translation …

Code-switching has seen growing interest in recent years as an important multilingual NLP
phenomenon. Generating code-switched text for data augmentation has been sufficiently …

Code-mixed text generation systems have found applications in many downstream tasks,
including speech recognition, translation and dialogue. A paradigm of these generation …

We describe models focused at the understudied problem of translating between
monolingual and code-mixed language pairs. More specifically, we offer a wide range of …